期刊
APPLICATIONS IN ENGINEERING SCIENCE
卷 10, 期 -, 页码 -出版社
ELSEVIER
DOI: 10.1016/j.apples.2022.100097
关键词
Data -driven approaches; EVAR; Circulating biomarkers; Pulse wave imaging; Physics -based machine learning; Digital twin
资金
- National Heart, Lung, and Blood Institute of the National Institutes of Health [R01HL115185, R21HL113857]
- National Science Foundation (NSF) [CMMI-1150376, ECCS- 2103434]
Ultrasound imaging is important in detecting abdominal aortic aneurysms, but it is only recommended for men aged 65-75 with a smoking history and not recommended for women. New technologies and methods like personalized medicine and data-driven approaches have the potential to make breakthroughs in the detection of small AAAs, monitoring patients during follow-ups, predicting AAA growth, assessing rupture risk, and post-surgical prognosis for AAA patient management.
Ultrasound imaging has long been playing a central role in detecting abdominal aortic aneurysms (AAAs). With a recent trend of reducing prevalence of AAAs, ultrasound screening is only recommended for men aged 65 to 75 years with previous smoking history, and a national level of a screening program for women is currently not recommended in the US. In the 2000s, several research groups demonstrated the utility of finite element stress analysis using patient-specific images, which was promising for an accurate assessment of the rupture risk, but physical models remain to be enhanced by considering patient variability and multi-physical characteristics. This review aims to provide a survey of emerging and alternative technologies and new methodologies, such as personalized medicine and data-driven approaches, that may make potential breakthroughs on detection of small AAAs, monitoring of patients during the follow-ups, prediction of AAA growth, assessment of the rupture risk, and post-surgical prognosis for AAA patient management.
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